Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.

Overview: Interpretability tools make machine learning models more transparent by displaying how each feature influences ...

In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...

Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...

Scholars analyze how the use of machine learning could reshape EPA drinking water standards.

NITK develops SVALSA, a machine learning-based landslide warning system for the Western Ghats, enhancing disaster ...

Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited ...

A new study published in the International Journal of General Medicine showed that physicians may reliably estimate the ...

AI model using deep transfer learning – the most advanced form of machine learning – predicted with 92 % accuracy spoken ...

Antimicrobial resistance (AMR) is an increasingly dangerous problem affecting global health. In 2019 alone, ...